390020 DK PhD-M: Management Decision Making (2019W)
Prüfungsimmanente Lehrveranstaltung
Labels
service email address: opim.bda@univie.ac.at
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 16.09.2019 09:00 bis Mo 23.09.2019 12:00
- Anmeldung von Do 26.09.2019 09:00 bis Fr 27.09.2019 12:00
- Abmeldung bis Mo 14.10.2019 12:00
Details
max. 15 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
PLEASE NOTE: The session on the 2.12. is cancelled. The substitute session takes place on FRIDAY, 13.12., at 15:00.
- Montag 14.10. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Montag 21.10. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Montag 28.10. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Montag 04.11. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Montag 11.11. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Montag 25.11. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Montag 09.12. 15:00 - 18:15 Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Stock
- Freitag 13.12. 15:00 - 16:30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Montag 16.12. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Montag 13.01. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Montag 20.01. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Montag 27.01. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Classroom work and exercises (20%)
Final exam (40%)
Research project or survey paper (at the student's choice) (40%)
Final exam (40%)
Research project or survey paper (at the student's choice) (40%)
Mindestanforderungen und Beurteilungsmaßstab
As a PhD course, this course goes beyond a practical knowledge of methods of decision analysis. Students should be able to understand the inherent logic of models of decision analysis and their relation to fundamental assumptions about rationality as well as the inherent limitations implied by these assumptions. This should enable students to select and apply the appropriate methods for their own research work.
Prüfungsstoff
The course uses a blend of e-learning based self instruction and classroom teaching. Teaching notes and training material are provided in advance on the e-learning platform, students are expected to study this material before class. Classroom lectures and discussions will be used to strengthen the students' understanding of the material.
Literatur
Lecture notes containing references will be available on Moodle
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mo 07.09.2020 15:22
2 Multidimensional evaluation Dominance and efficiency
3 Decisions under risk: Introduction to expected utility theory
4 Applications and extensions to expected utility theory
5 Dynamic decision problems and the value of information
6 Multicriteria decisions: Additive models
7 Decisions under incomplete information and sensitivity analysis